Challenges related to automated driving are no longer focused on just the construction of
such automated vehicles (AVs) but also on assuring the safety of operation. Recent …

Abstract 3D lane detection from monocular images is a fundamental yet challenging task in
autonomous driving. Recent advances primarily rely on structural 3D surrogates (eg, bird's …

Researchers have made many attempts to apply reinforcement learning (RL) to learn to fly
aircraft in recent years. However, existing RL strategies are usually not safe (eg, can lead to …

In this study, we propose an aerial rendezvous method to facilitate the recovery of
unmanned aerial vehicles (UAVs) using carrier aircrafts, which is an important capability for …

Reinforcement Learning is a highly active research field with promising advancements. In
the field of autonomous driving, however, often very simple scenarios are being examined …

In the rapidly evolving domain of electrical power systems, the Volt-VAR optimization (VVO)
is increasingly critical, especially with the burgeoning integration of renewable energy …

View Video Presentation: https://doi. org/10.2514/6.2023-4215. vid By designing flight paths
that can minimize fuel consumption and noise, flight trajectory optimization has been …

Abstract [eng] Irregularly-sampled time series occur in many real-world applications, such as
robots movement, astronomy, medicine. In this master's thesis, we concentrate on learning …

Increased driving safety is a potential benefit of introducing higher levels of automation in
vehicles. Compared to human drivers, an Automated Driving System (ADS) can leverage the …

This paper proposes a integrated guidance and control method for an underactuated dual-
arm space manipulator to transfer near the Space Station (SS) to the target position and …